Scalable and efficient analysis of data

Using novel methods and algorithms, our experts can conduct Big Data analysis for compute clusters or high-performance compute infrastructure (i.e. supercomputers). They can also implement new analytical approaches and algorithms for commercial applications - such as spatial analytics for Transport for London or medical analytics for start-ups - plus scientific applications in medicine, neuroscience, physics and more.

Big Data and Statistical Machine Learning

Our experts are developing machine learning techniques that can handle modern data types, such as free text, and draw on statistical and computational intelligence techniques to navigate vast amounts of information, like distributed databases or data streams, with minimal human supervision.

They have also developed Bayesian anomaly detection methods to protect high volume data streams and large dynamic computer networks against cyber-attacks and fraudulent activity. See Statistical Cyber Security Analytics

Dr Roberto Trotta - develops advanced statistical and numerical methods for the analysis and interpretation of complex data from astrophysics, cosmology and particle physics which underpin statistical consultancy and custom-made data analysis solutions. He also works as a scientific consultant with museums, writers, film makers and artists, providing the help and support they need to make their artistic creations scientifically sound.

Privacy - and use of data

Large-scale datasets (such as mobile phone logs, credit card usage, browsing metadata, membership or customer sales information) offer huge insight into the location, habits and requirements of people without the need for questionnaires. However, anonymity and privacy issues require organisations to gather and store it securely, thus restricting the use of data that could plot trends, identify needs and better understand societies on a large scale.

Our experts can help with solutions to secure your data and use machine learning techniques to gain invaluable insight - and data driven customer segmentation for marketeers. Some examples...

using behavioural indicators they can predict people's personality up to 1.7x better than random to help organisations better understand their customers.

using telco data to provide an insight into the spread of infectious diseases, strategies into micro-target outreach and driving health-seeking behaviour.

What's more, data from separate datasets can be matched to provide a broader and more informed picture of an individual. For example, by matching data from different departments or registers within an organisation, they can create an overarching profile of a customer so their needs can be quickly and effectively assessed.